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PRIor Myocardial Infarction Identification on Electrocardiogram

Prospective Cohort Study of Prior Myocardial Infarction Identification on Electrocardiogram: the PRIME Cohort Study

Status
Enrolling by invitation
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06811194
Acronym
PRIME
Enrollment
12000
Registered
2025-02-06
Start date
2025-02-20
Completion date
2031-02-20
Last updated
2025-02-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Prior Myocardial Infarction

Brief summary

Abstract Background: Chronic myocardial infarction (MI) is a serious cardiovascular disease associated with high mortality rates, making early diagnosis and timely intervention essential for improving patient outcomes. However, some patients may present without clear symptoms or relevant medical histories, complicating the diagnostic process. Currently, diagnosis predominantly relies on electrocardiograms (ECGs) and imaging tests. Although cardiac magnetic resonance imaging (MRI) is regarded as the gold standard, its high cost and complexity hinder its clinical application. Consequently, there is an urgent need for new ECG diagnostic criteria to mitigate the risks of misdiagnosis and missed diagnoses. Objective: This study aims to explore new diagnostic criteria to enhance the accuracy of ECG diagnoses for chronic MI. Methods: This research is a prospective, multicenter cohort study designed to assess the impact of newly developed ECG diagnostic criteria on the accuracy of chronic myocardial infarction (MI) diagnoses. The study spans a 60-month period, including a 12-month patient enrollment phase. Participants will comprise individuals aged 35 to 85 who meet the inclusion criteria: those diagnosed with chronic myocardial infarction via ECG, those with a definitive history of MI (≥3 months), or individuals clinically suspected of having coronary artery disease with at least two coronary risk factors. Data collection will include clinical symptoms, signs, ECG findings, and cardiac magnetic resonance (CMR) findings, the latter serving as a primary endpoint. Follow-up will focus on changes in patients' symptoms and ECG assessments. Statistical analysis software will be employed to evaluate the influence of the new diagnostic criteria on rates of missed and misdiagnosis.

Detailed description

Abstract Background: Chronic myocardial infarction (MI) is a serious cardiovascular disease associated with high mortality rates, making early diagnosis and timely intervention essential for improving patient outcomes. However, some patients may present without clear symptoms or relevant medical histories, complicating the diagnostic process. Currently, diagnosis predominantly relies on electrocardiograms (ECGs) and imaging tests. Although cardiac magnetic resonance imaging (MRI) is regarded as the gold standard, its high cost and complexity hinder its clinical application. Consequently, there is an urgent need for new ECG diagnostic criteria to mitigate the risks of misdiagnosis and missed diagnoses. Objective: This study aims to explore new diagnostic criteria to enhance the accuracy of ECG diagnoses for chronic MI. Methods: This research is a prospective, multicenter cohort study designed to assess the impact of newly developed ECG diagnostic criteria on the accuracy of chronic myocardial infarction (MI) diagnoses. The study spans a 60-month period, including a 12-month patient enrollment phase. Participants will comprise individuals aged 35 to 85 who meet the inclusion criteria: those diagnosed with chronic myocardial infarction via ECG, those with a definitive history of MI (≥3 months), or individuals clinically suspected of having coronary artery disease with at least two coronary risk factors. Data collection will include clinical symptoms, signs, ECG findings, and cardiac magnetic resonance (CMR) findings, the latter serving as a primary endpoint. Follow-up will focus on changes in patients' symptoms and ECG assessments. Statistical analysis software will be employed to evaluate the influence of the new diagnostic criteria on rates of missed and misdiagnosis.

Interventions

None listed

Sponsors

The Third People's Hospital of Chengdu
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
35 Years to 85 Years
Healthy volunteers
Yes

Inclusion criteria

* Aged between 35 and 85 years. * Patients must meet at least one of the following conditions: * Diagnosis of prior MI based on ECG (as per the fourth universal definition of MI). * History of prior MI (≥3 months post-MI). * Any clinical suspicion of coronary artery disease (CAD) with at least two of the following risk factors: Male age \>50 years or female age \>60 years. Diabetes mellitus. Hypertension. Hypercholesterolemia requiring medication. Family history of premature CAD (first-degree relatives: male ≤55 years, female ≤65 years). Body mass index (BMI) ≥30 kg/m². History of peripheral vascular disease. History of coronary artery intervention or bypass surgery. Informed consent obtained

Exclusion criteria

* Life expectancy \<1 year due to non-cardiovascular diseases. * Contraindications to cardiac MRI or inability to complete the examination. * History of non-ischemic cardiomyopathy. * History of heart transplantation. * Acute MI within the past 30 days. * During pregnancy.

Design outcomes

Primary

MeasureTime frameDescription
Cardiovascular death or nonfatal MI.60 Months after EnrollmentPrimary outcome: cardiovascular death or nonfatal MI occurred during the 60-month follow-up after enrollment.

Secondary

MeasureTime frameDescription
A composite of cardiovascular death, nonfatal MI, hospitalization for unstable angina or congestive heart failure, and late unplanned CABG.60 Months after EnrollmentSecondary outcome was defined by a composite of cardiovascular death, nonfatal MI, hospitalization for unstable angina or congestive heart failure, and late unplanned CABG.

Countries

China

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026